An application of automated reasoning in natural language question answering

被引:18
|
作者
Furbach, Ulrich [1 ]
Gloeckner, Ingo [2 ]
Pelzer, Bjoern [1 ]
机构
[1] Univ Koblenz Landau, Artificial Intelligence Res Grp, D-56070 Koblenz, Germany
[2] Univ Hagen, D-59084 Hagen, Germany
关键词
Question answering; theorem prover;
D O I
10.3233/AIC-2010-0461
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The LogAnswer system is an application of automated reasoning to the field of open domain question answering. In order to find answers to natural language questions regarding arbitrary topics, the system integrates an automated theorem prover in a framework of natural language processing tools. The latter serve to construct an extensive knowledge base automatically from given textual sources, while the automated theorem prover makes it possible to derive answers by deductive reasoning. In the paper, we discuss the requirements to the prover that arise in this application, especially concerning efficiency and robustness. The proposed solution rests on incremental reasoning, relaxation of the query (if no proof of the full query is found), and other techniques. In order to improve the robustness of the approach to gaps of the background knowledge, the results of deductive processing are combined with shallow linguistic features by machine learning.
引用
收藏
页码:241 / 265
页数:25
相关论文
共 50 条
  • [31] Automated Question Answering Assistant
    Kitukale, Rutuja
    Pai, Nachiketh
    Nerkar, Prathamesh
    Shirke, Archana
    Jose, Jerin
    2021 INTERNATIONAL CONFERENCE ON INNOVATIVE TRENDS IN INFORMATION TECHNOLOGY (ICITIIT), 2021,
  • [32] Knowledge-Augmented Visual Question Answering With Natural Language Explanation
    Xie, Jiayuan
    Cai, Yi
    Chen, Jiali
    Xu, Ruohang
    Wang, Jiexin
    Li, Qing
    IEEE TRANSACTIONS ON IMAGE PROCESSING, 2024, 33 : 2652 - 2664
  • [33] Natural Language Question/Answering: Let Users Talk With The Knowledge Graph
    Zheng, Weiguo
    Cheng, Hong
    Zou, Lei
    Yu, Jeffrey Xu
    Zhao, Kangfei
    CIKM'17: PROCEEDINGS OF THE 2017 ACM CONFERENCE ON INFORMATION AND KNOWLEDGE MANAGEMENT, 2017, : 217 - 226
  • [34] HiTab: A Hierarchical Table Dataset for Question Answering and Natural Language Generation
    Cheng, Zhoujun
    Dong, Haoyu
    Wang, Zhiruo
    Jia, Ran
    Guo, Jiaqi
    Gao, Yan
    Han, Shi
    Lou, Jian-Guang
    Zhang, Dongmei
    PROCEEDINGS OF THE 60TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (ACL 2022), VOL 1: (LONG PAPERS), 2022, : 1094 - 1110
  • [35] LAMBADA: Backward Chaining for Automated Reasoning in Natural Language
    Kazemi, Mehran
    Kim, Najoung
    Bhatia, Deepti
    Xu, Xin
    Ramachandran, Deepak
    PROCEEDINGS OF THE 61ST ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS, ACL 2023, VOL 1, 2023, : 6547 - 6568
  • [36] Knowledge-Augmented Visual Question Answering With Natural Language Explanation
    Xie, Jiayuan
    Cai, Yi
    Chen, Jiali
    Xu, Ruohang
    Wang, Jiexin
    Li, Qing
    IEEE Transactions on Image Processing, 2024, 33 : 2652 - 2664
  • [37] High Accuracy Question Answering via Hybrid Controlled Natural Language
    Gao, Tiantian
    Fodor, Paul
    Kifer, Michael
    2018 IEEE/WIC/ACM INTERNATIONAL CONFERENCE ON WEB INTELLIGENCE (WI 2018), 2018, : 17 - 24
  • [38] Natural language Question - Answering model applied to document retrieval system
    Dang, Nguyen Tuan
    Tuyen, Do Thi Thanh
    World Academy of Science, Engineering and Technology, 2009, 39 : 36 - 39
  • [39] Semantic Understanding of Natural Language Stories for Near Human Question Answering
    Jamil, Hasan M.
    Oduro-Afriyie, Joel
    FLEXIBLE QUERY ANSWERING SYSTEMS, 2019, 11529 : 215 - 227
  • [40] Evaluating Natural Language Understanding Services for Conversational Question Answering Systems
    Braun, Daniel
    Mendez, Adrian Hernandez
    Matthes, Florian
    Langen, Manfred
    18TH ANNUAL MEETING OF THE SPECIAL INTEREST GROUP ON DISCOURSE AND DIALOGUE (SIGDIAL 2017), 2017, : 174 - 185